Uses of Interface
elki.clustering.kmedoids.KMedoidsClustering

Packages that use KMedoidsClustering

Package	Description
elki.clustering.kmedoids	K-medoids clustering (PAM).
elki.clustering.kmedoids.initialization
elki.clustering.silhouette	Silhouette clustering algorithms.

Uses of KMedoidsClustering in elki.clustering.kmedoids

Classes in elki.clustering.kmedoids that implement KMedoidsClustering

Modifier and Type	Class	Description
class	AlternatingKMedoids<O>	A k-medoids clustering algorithm, implemented as EM-style batch algorithm; known in literature as the "alternate" method.
class	CLARA<V>	Clustering Large Applications (CLARA) is a clustering method for large data sets based on PAM, partitioning around medoids (PAM) based on sampling.
class	CLARANS<O>	CLARANS: a method for clustering objects for spatial data mining is inspired by PAM (partitioning around medoids, PAM) and CLARA and also based on sampling.
class	EagerPAM<O>	Variation of PAM that eagerly performs all swaps that yield an improvement during an iteration.
class	FastCLARA<V>	Clustering Large Applications (CLARA) with the FastPAM improvements, to increase scalability in the number of clusters.
class	FastCLARANS<V>	A faster variation of CLARANS, that can explore O(k) as many swaps at a similar cost by considering all medoids for each candidate non-medoid.
class	FasterCLARA<O>	Clustering Large Applications (CLARA) with the FastPAM improvements, to increase scalability in the number of clusters.
class	FasterPAM<O>	Variation of FastPAM that eagerly performs any swap that yields an improvement during an iteration.
class	FastPAM<O>	FastPAM: An improved version of PAM, that is usually O(k) times faster.
class	FastPAM1<O>	FastPAM1: A version of PAM that is O(k) times faster, i.e., now in O((n-k)²).
class	PAM<O>	The original Partitioning Around Medoids (PAM) algorithm or k-medoids clustering, as proposed by Kaufman and Rousseeuw; a largely equivalent method was also proposed by Whitaker in the operations research domain, and is well known by the name "fast interchange" there.
class	ReynoldsPAM<O>	The Partitioning Around Medoids (PAM) algorithm with some additional optimizations proposed by Reynolds et al.
class	SingleAssignmentKMedoids<O>	K-medoids clustering by using the initialization only, then assigning each object to the nearest neighbor.

Uses of KMedoidsClustering in elki.clustering.kmedoids.initialization

Fields in elki.clustering.kmedoids.initialization declared as KMedoidsClustering

Modifier and Type	Field	Description
private KMedoidsClustering<O>	KMedoidsKMedoidsInitialization.inner	Inner k-medoids clustering to use.
private KMedoidsClustering<O>	KMedoidsKMedoidsInitialization.Par.inner	Clustering algorithm

Constructors in elki.clustering.kmedoids.initialization with parameters of type KMedoidsClustering

Constructor	Description
KMedoidsKMedoidsInitialization(KMedoidsClustering<O> inner)	Constructor.

Uses of KMedoidsClustering in elki.clustering.silhouette

Classes in elki.clustering.silhouette that implement KMedoidsClustering

Modifier and Type	Class	Description
class	FasterMSC<O>	Fast and Eager Medoid Silhouette Clustering.
class	FastMSC<O>	Fast Medoid Silhouette Clustering.
class	PAMMEDSIL<O>	Clustering to optimize the Medoid Silhouette coefficient with a PAM-based swap heuristic.
class	PAMSIL<O>	Clustering to optimize the Silhouette coefficient with a PAM-based swap heuristic.